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Dumane et al. J Cancer Metastasis Treat 2019;5:42 I http://dx.doi.org/10.20517/2394-4722.2019.08 Page 9 of 10

All the cases for training and validation were chosen without any pre-selection criteria. The limitation of
this study is that it was trained and tested only with a maximum of 4 lesions per case. This was because
in the cohort of patients that were treated, there were only 3 cases that had > 4 lesions, which essentially is
not enough to train a model. As we treat and acquire data on more patients that have > 4 lesions, these can
be incorporated into the model. Another limitation of this study is that the cases used for training were of
smaller volume and were typically peripheral and far away from critical organs as well as from each other.
This model therefore cannot be used for lesions that are overlapping with critical organs or for lesions in
close proximity of each other.

The plans were slightly more inhomogeneous compared to the original clinical plans. This could be due to
the fact that we used a line objective for the DVH in addition to the maximum point dose objective for the
critical organ. Although the DVH for the PTV shows a longer tail, the dose inhomogeneity is contained
within the target. We anticipate that with more training cases, the dosimetric results will improve. The GI
was also slightly higher with the KBP plans than the recommended value of < 4. However the plans were
dosimetrically very similar. Moreover, when a typical clinical plan would take at least 2 to 3 h to complete,
the RapidPlan gave a clinically acceptable result in under 30 min.

The quality of the treatment plan generated by RapidPlan can only be as good as that of the treatment plans
used to generate the DVH estimation model. Other technologies such as Hyperarc® are available from Varian
Medical Systems that can automate SRS planning, however, they are currently unavailable with RapidPlan.
This study demonstrates the feasibility of using RapidPlan as it pertains to a limited number of lesions (≤ 4).
Going forward, we plan on expanding its training and application to > 4 lesions. In the future we plan to
expand this to > 4 lesions and perform a comparison with plans generated using Hyperarc.

In conclusion, we have developed an efficient method for treatment planning of multiple cranial SRS lesions
using VMAT and a single isocenter. This is a step not only towards a reducing the treatment planning time
but also providing the planner a guide on the achievable dose distribution for the given case, thereby helping
to standardize the quality of the treatment plans.

DECLARATIONS
Authors’ contributions
Built the model, studied design, performed the dosimetric and statistical analysis: Dumane VA
Planned the clinical cases that were used for training and testing while building the model: Tseng TC
Designed the database used for obtaining patient treated with SRS using VMAT on Eclipse planning system:
Sheu RD
Provided input towards study design and performed statistical analysis: Lo YC
Contributed towards writing the manuscript: Dumane VA, Tseng TC, Sheu RD, Lo YC, Gupta V, Saitta A,
Rosenzweig KE, Green S
Participated in the study design, contouring of all the target volumes and critical organs, reviewing plans:
Green S

Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on
reasonable request.

Financial support and sponsorship
None.